With the increasing rate of development in urban areas globally, it is often difficult for even locals to keep track of rapidly changing neighborhoods. The advent of the internet resulted in an overabundance of data to sift through to find a neighborhood to match your preferences. The ease and accuracy of Mr. Roger's Neighborhood will not only keep locals connected to the city's culture and lifestyle, but also allow tourists to explore different regions according to their interests.

What It Does

This web application lists and evaluates prominent neighborhoods of cities according to user preferences, depending on desired amenity, distance, and priority. Using the dataset from the Yelp API on business locations and reviews, the application scores different areas based on a weighted formula calculating percentage match to user input.

How We Built It

As the application depended on our dataset, much time was spent brainstorming how to best use the data we had to provide the most accurate evaluation for the user. We discussed (and set aside) several potential factors to consider in our matching formula, such as ratings, reviews, and adding public transportation distance instead of just walking distance. We selected for the most feasible and relevant details: amenity categories and the respective priority assignations.

Challenges We Ran Into

First, we realized that our original idea (finding a specific location catering to several desired amenities) would be extremely difficult to implement, especially when considering the time constraints of a hackathon. We limited our scope to focusing on the boundaries of defined city neighborhoods to reduce the amount of computing power necessary. We also had to normalize the data in terms of accents to reduce duplications and inaccuracies.

Accomplishments that We're Proud of

We successfully created a web application that leverages a massive dataset to evaluate a city's neighborhoods based on user preferences. A rather accurate formula allows for weighting the user's priorities for one amenity over another as well as density of amenities within a close walking radius of the center of the neighborhood.

What's Next for Mr. Roger's Neighborhood

Currently, our web application only searches through prominent neighborhoods in downtown Montreal. To be more widely accessible, datasets for other cities should be added to this application's database. This idea could also be developed into a mobile application to increase user convenience and usage.

What's next for Mr. Roger's Neighborhood

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